Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "30" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 58 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 56 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459873 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.775701 | -1.381342 | -0.730442 | -0.758362 | 0.057395 | -0.698710 | 12.464391 | 0.386240 | 0.7036 | 0.6841 | 0.3696 | nan | nan |
| 2459872 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.784523 | -1.417095 | -0.342252 | -0.936020 | 2.221220 | -0.697535 | 23.287042 | 0.732172 | 0.6947 | 0.6891 | 0.3791 | nan | nan |
| 2459871 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.132723 | -1.202690 | 0.987720 | -0.858481 | 2.257653 | -1.256008 | 11.933848 | -0.023279 | 0.7025 | 0.6875 | 0.3746 | nan | nan |
| 2459870 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.567230 | -1.114690 | 1.340106 | -0.860594 | 0.088729 | 0.131632 | 30.249161 | 0.732076 | 0.7059 | 0.6904 | 0.3776 | nan | nan |
| 2459869 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.521325 | -1.370417 | 5.005668 | -0.957314 | -0.257075 | -0.823459 | 3.257247 | -0.733759 | 0.7220 | 0.7121 | 0.3721 | nan | nan |
| 2459868 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.053476 | -1.131520 | 1.108063 | -1.274548 | 26.474534 | -1.200500 | 23.227067 | 1.468838 | 0.6969 | 0.6865 | 0.3889 | nan | nan |
| 2459867 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 1.904421 | -1.078022 | 0.679145 | -1.182588 | 0.238550 | -0.876967 | 10.998923 | 0.735630 | 0.7062 | 0.6886 | 0.3858 | nan | nan |
| 2459866 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.348249 | -1.013629 | 0.907619 | -0.837050 | 1.020974 | -0.959317 | 16.642497 | 0.863428 | 0.7064 | 0.6930 | 0.3805 | nan | nan |
| 2459865 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 1.004908 | -0.574047 | 0.274650 | -1.092353 | -0.215993 | -0.789811 | 9.748402 | 0.381663 | 0.7318 | 0.7189 | 0.3469 | nan | nan |
| 2459864 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.103454 | -1.617171 | 1.880738 | 0.870598 | -0.130672 | -0.281899 | 25.067023 | 2.108951 | 0.7002 | 0.6819 | 0.3996 | nan | nan |
| 2459863 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.214924 | -1.325397 | 0.760065 | 0.690009 | -0.635726 | -0.148139 | 10.707526 | 0.699938 | 0.6938 | 0.6720 | 0.3924 | nan | nan |
| 2459862 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.536321 | -1.497361 | 1.380565 | 0.883851 | -0.189457 | -0.069729 | 4.295324 | 0.073318 | 0.6803 | 0.7025 | 0.4042 | nan | nan |
| 2459861 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.440334 | -1.137825 | 0.780401 | 0.874187 | -0.026758 | 0.411667 | 14.301028 | 0.944300 | 0.7050 | 0.6876 | 0.3964 | nan | nan |
| 2459860 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.034206 | -1.233487 | 0.921410 | 0.456368 | -0.696904 | -0.862580 | 9.026249 | -0.475083 | 0.7162 | 0.6849 | 0.3968 | nan | nan |
| 2459859 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.909323 | -1.054666 | 0.655436 | 0.856677 | -0.177283 | 0.318604 | 8.872938 | -0.002508 | 0.7185 | 0.6870 | 0.3969 | nan | nan |
| 2459858 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.686766 | -1.051241 | 0.764606 | 0.825849 | -0.485394 | 1.037251 | 15.955391 | 0.306754 | 0.7285 | 0.6946 | 0.4064 | 2.622814 | 2.493992 |
| 2459857 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.137781 | -0.825694 | 0.017448 | -0.137521 | 0.419390 | 0.509951 | 10.007759 | 1.935413 | 0.0253 | 0.0250 | 0.0004 | nan | nan |
| 2459856 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.43% | 0.00% | -1.430670 | -1.722743 | 0.615474 | 0.460274 | -0.544766 | 0.420839 | 3.011847 | -0.453489 | 0.7259 | 0.7078 | 0.3951 | 1.648414 | 1.470342 |
| 2459855 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 75.534623 | 75.091620 | inf | inf | 4363.457479 | 4363.366637 | 4164.625561 | 4163.721597 | 0.0069 | 0.0099 | 0.0004 | 0.000000 | 0.000000 |
| 2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.205114 | -1.842815 | 0.117423 | -0.145891 | -0.366893 | 0.326326 | 6.428296 | 0.395992 | 0.7222 | 0.7483 | 0.4293 | 2.527649 | 2.357077 |
| 2459853 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.284029 | -1.323361 | 0.174829 | -0.050614 | -0.236176 | -0.729193 | 13.701699 | 0.078479 | 0.7440 | 0.6985 | 0.4144 | 2.789460 | 2.598811 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 0.54% | -0.354273 | -0.865691 | 0.508355 | -0.338423 | -0.416452 | -1.196075 | 0.329028 | -0.529674 | 0.8352 | 0.8418 | 0.2337 | 2.623216 | 2.568499 |
| 2459851 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.297935 | -0.879476 | -0.129911 | -0.138644 | 0.217384 | -0.678426 | 7.818962 | -0.033164 | 0.7620 | 0.7539 | 0.3299 | 3.236996 | 3.194164 |
| 2459850 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.048214 | -1.380375 | -0.093056 | -0.091468 | -0.114980 | -0.335554 | 21.172282 | 0.247266 | 0.7449 | 0.7568 | 0.3463 | 2.686679 | 2.513970 |
| 2459849 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.230180 | -1.525932 | -0.221486 | 0.065710 | -0.371565 | 0.232060 | 8.204039 | 0.089091 | 0.7471 | 0.7503 | 0.3554 | 3.395252 | 2.963083 |
| 2459848 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.539499 | -1.219033 | 1.162600 | -1.173416 | -0.602165 | -1.068705 | 8.380763 | -0.473136 | 0.7211 | 0.7544 | 0.3710 | 2.824408 | 2.663309 |
| 2459847 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.170020 | -0.964175 | 1.522203 | -0.902884 | 0.103091 | -0.613997 | 12.266691 | -0.192116 | 0.7179 | 0.6912 | 0.4251 | 2.763787 | 2.756808 |
| 2459846 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.053829 | -0.874056 | 2.399603 | -0.947547 | 1.618448 | -0.197922 | 4.141222 | -0.039770 | 0.8465 | 0.6930 | 0.4714 | 3.086520 | 3.173703 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.975023 | -1.157949 | 2.067629 | -0.712601 | 0.250600 | 0.211950 | 13.991537 | -0.543906 | 0.7436 | 0.7662 | 0.3572 | 7.145209 | 6.324221 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 1.621403 | -0.197070 | -0.630744 | -0.322080 | 1.471871 | 1.706926 | 11.944439 | 2.839781 | 0.0248 | 0.0247 | 0.0004 | nan | nan |
| 2459843 | digital_ok | 100.00% | 0.66% | 0.66% | 0.00% | 100.00% | 0.00% | -0.251126 | -1.289823 | 3.378764 | -0.793178 | 9.510200 | -0.051219 | 2.842146 | -0.294379 | 0.7438 | 0.7608 | 0.3763 | 3.555006 | 3.453905 |
| 2459842 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.983147 | -0.679405 | 2.125623 | 0.685452 | -0.002276 | 0.487096 | 1.471696 | 0.370314 | 0.7365 | 0.6558 | 0.2692 | 1.946640 | 1.885550 |
| 2459841 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 4.011404 | -0.620182 | 0.255598 | -1.030054 | 41.673645 | 2.530882 | 1.854411 | 2.719422 | 0.0246 | 0.0245 | 0.0005 | nan | nan |
| 2459840 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.863699 | -0.286343 | -1.317203 | -1.444304 | 1.616618 | 1.413163 | -0.124628 | 2.059455 | 0.0236 | 0.0236 | 0.0006 | nan | nan |
| 2459839 | digital_ok | 0.00% | - | - | - | - | - | -1.125189 | -0.375068 | -0.197769 | -0.108181 | 0.645467 | 0.295903 | -0.261586 | 2.086783 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.381134 | -0.577491 | 0.282216 | -0.549091 | -0.521897 | -0.218540 | 10.709946 | 0.297344 | 0.7289 | 0.6776 | 0.4180 | 4.772462 | 4.713662 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0380 | 0.0375 | 0.0023 | nan | nan |
| 2459835 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -1.266579 | -1.300783 | -0.455075 | -0.010309 | 6.222181 | 6.311743 | 35.845686 | 22.802739 | 0.0370 | 0.0371 | 0.0023 | nan | nan |
| 2459833 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 1.343575 | 2.136819 | -0.704933 | -0.160039 | 13.550888 | 16.573601 | 55.601854 | 48.673665 | 0.0320 | 0.0367 | 0.0030 | nan | nan |
| 2459832 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
| 2459831 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -1.085672 | -0.480268 | -0.002702 | 0.022453 | 0.719597 | 0.074985 | -0.200220 | 1.724959 | 0.0278 | 0.0310 | 0.0010 | nan | nan |
| 2459830 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.436193 | 0.146932 | 0.297627 | -0.895334 | -0.031853 | -0.552044 | 13.693569 | 0.627987 | 0.7970 | 0.5063 | 0.5940 | 6.142561 | 6.668801 |
| 2459829 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.630690 | -0.514255 | 0.378077 | -0.369303 | -0.439570 | -0.031398 | 31.627271 | 2.340068 | 0.7395 | 0.6381 | 0.4394 | 0.900616 | 0.898108 |
| 2459828 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.371793 | -0.229500 | -0.181119 | -0.077978 | -0.317467 | 0.094005 | 14.513027 | 1.803096 | 0.7986 | 0.5261 | 0.5689 | 4.711004 | 4.233313 |
| 2459827 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.767485 | -0.034909 | 0.231554 | -0.549992 | 2.808195 | 0.592458 | 9.903250 | -0.569960 | 0.7513 | 0.6459 | 0.4413 | 8.217051 | 10.045244 |
| 2459826 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.403762 | -0.103128 | -0.459196 | -0.837233 | -0.355210 | 1.987433 | 7.236491 | 1.100022 | 0.7945 | 0.5479 | 0.5423 | 10.981437 | 14.249079 |
| 2459825 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.887219 | 0.077471 | -0.616337 | -0.733705 | 0.698155 | -0.347839 | 7.837576 | 0.137726 | 0.7941 | 0.5507 | 0.5463 | 4.234505 | 3.813181 |
| 2459824 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.124021 | -0.253156 | -0.446498 | -0.721351 | 5.467165 | 3.413469 | 11.399778 | 8.624690 | 0.6871 | 0.6782 | 0.4082 | 4.446352 | 6.275191 |
| 2459823 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.094147 | -0.357138 | 0.173846 | -0.827760 | 0.255894 | -0.021975 | 13.556504 | 0.381534 | 0.7533 | 0.6057 | 0.5024 | 6.818279 | 6.920826 |
| 2459822 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.879364 | 0.172485 | 0.098233 | -0.442135 | -0.478864 | 0.333374 | 4.556629 | -0.719967 | 0.8014 | 0.5817 | 0.5446 | 4.493485 | 4.386979 |
| 2459821 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.302348 | 0.355354 | -0.139940 | -0.829650 | 3.107132 | 2.602256 | 3.550737 | 1.841631 | 0.7991 | 0.6089 | 0.5284 | 2.152489 | 1.915417 |
| 2459820 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.536181 | -0.438914 | -0.339955 | -0.479258 | -0.130670 | 2.300674 | 10.425166 | 0.822505 | 0.7721 | 0.6831 | 0.4244 | 4.736645 | 5.465844 |
| 2459817 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.394901 | -0.041643 | -0.543360 | -0.671958 | 0.192475 | 0.811400 | 3.400272 | 1.020329 | 0.8208 | 0.6787 | 0.4994 | 2.084224 | 1.972904 |
| 2459816 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.110596 | 0.188747 | 0.616287 | -0.933839 | 0.607607 | -0.146862 | 13.490380 | 0.708062 | 0.8462 | 0.6021 | 0.5818 | 3.724818 | 3.790440 |
| 2459815 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.472592 | -0.128359 | 0.307634 | -1.010720 | 0.924300 | 1.454898 | 8.258613 | 1.551020 | 0.8107 | 0.6828 | 0.5091 | 4.410142 | 4.682017 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 12.464391 | 0.775701 | -1.381342 | -0.730442 | -0.758362 | 0.057395 | -0.698710 | 12.464391 | 0.386240 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 23.287042 | -1.417095 | 0.784523 | -0.936020 | -0.342252 | -0.697535 | 2.221220 | 0.732172 | 23.287042 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 11.933848 | -1.202690 | 0.132723 | -0.858481 | 0.987720 | -1.256008 | 2.257653 | -0.023279 | 11.933848 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 30.249161 | 2.567230 | -1.114690 | 1.340106 | -0.860594 | 0.088729 | 0.131632 | 30.249161 | 0.732076 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Power | 5.005668 | -0.521325 | -1.370417 | 5.005668 | -0.957314 | -0.257075 | -0.823459 | 3.257247 | -0.733759 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Variability | 26.474534 | 0.053476 | -1.131520 | 1.108063 | -1.274548 | 26.474534 | -1.200500 | 23.227067 | 1.468838 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 10.998923 | 1.904421 | -1.078022 | 0.679145 | -1.182588 | 0.238550 | -0.876967 | 10.998923 | 0.735630 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 16.642497 | -1.013629 | 2.348249 | -0.837050 | 0.907619 | -0.959317 | 1.020974 | 0.863428 | 16.642497 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 9.748402 | 1.004908 | -0.574047 | 0.274650 | -1.092353 | -0.215993 | -0.789811 | 9.748402 | 0.381663 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 25.067023 | -1.617171 | -1.103454 | 0.870598 | 1.880738 | -0.281899 | -0.130672 | 2.108951 | 25.067023 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 10.707526 | -1.214924 | -1.325397 | 0.760065 | 0.690009 | -0.635726 | -0.148139 | 10.707526 | 0.699938 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 4.295324 | -1.536321 | -1.497361 | 1.380565 | 0.883851 | -0.189457 | -0.069729 | 4.295324 | 0.073318 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 14.301028 | -1.137825 | -0.440334 | 0.874187 | 0.780401 | 0.411667 | -0.026758 | 0.944300 | 14.301028 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 9.026249 | -1.034206 | -1.233487 | 0.921410 | 0.456368 | -0.696904 | -0.862580 | 9.026249 | -0.475083 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 8.872938 | -0.909323 | -1.054666 | 0.655436 | 0.856677 | -0.177283 | 0.318604 | 8.872938 | -0.002508 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 15.955391 | -1.051241 | -0.686766 | 0.825849 | 0.764606 | 1.037251 | -0.485394 | 0.306754 | 15.955391 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 10.007759 | -0.825694 | -0.137781 | -0.137521 | 0.017448 | 0.509951 | 0.419390 | 1.935413 | 10.007759 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 3.011847 | -1.430670 | -1.722743 | 0.615474 | 0.460274 | -0.544766 | 0.420839 | 3.011847 | -0.453489 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | nn Power | inf | 75.091620 | 75.534623 | inf | inf | 4363.366637 | 4363.457479 | 4163.721597 | 4164.625561 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 6.428296 | -1.842815 | 0.205114 | -0.145891 | 0.117423 | 0.326326 | -0.366893 | 0.395992 | 6.428296 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 13.701699 | -1.323361 | -0.284029 | -0.050614 | 0.174829 | -0.729193 | -0.236176 | 0.078479 | 13.701699 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Power | 0.508355 | -0.354273 | -0.865691 | 0.508355 | -0.338423 | -0.416452 | -1.196075 | 0.329028 | -0.529674 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 7.818962 | 0.297935 | -0.879476 | -0.129911 | -0.138644 | 0.217384 | -0.678426 | 7.818962 | -0.033164 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 21.172282 | -0.048214 | -1.380375 | -0.093056 | -0.091468 | -0.114980 | -0.335554 | 21.172282 | 0.247266 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 8.204039 | -1.230180 | -1.525932 | -0.221486 | 0.065710 | -0.371565 | 0.232060 | 8.204039 | 0.089091 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 8.380763 | -1.219033 | 0.539499 | -1.173416 | 1.162600 | -1.068705 | -0.602165 | -0.473136 | 8.380763 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 12.266691 | -0.964175 | 2.170020 | -0.902884 | 1.522203 | -0.613997 | 0.103091 | -0.192116 | 12.266691 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 4.141222 | -1.053829 | -0.874056 | 2.399603 | -0.947547 | 1.618448 | -0.197922 | 4.141222 | -0.039770 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 13.991537 | -1.157949 | 0.975023 | -0.712601 | 2.067629 | 0.211950 | 0.250600 | -0.543906 | 13.991537 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 11.944439 | 1.621403 | -0.197070 | -0.630744 | -0.322080 | 1.471871 | 1.706926 | 11.944439 | 2.839781 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Variability | 9.510200 | -1.289823 | -0.251126 | -0.793178 | 3.378764 | -0.051219 | 9.510200 | -0.294379 | 2.842146 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Power | 2.125623 | -0.983147 | -0.679405 | 2.125623 | 0.685452 | -0.002276 | 0.487096 | 1.471696 | 0.370314 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Variability | 41.673645 | 4.011404 | -0.620182 | 0.255598 | -1.030054 | 41.673645 | 2.530882 | 1.854411 | 2.719422 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | nn Temporal Discontinuties | 2.059455 | -0.863699 | -0.286343 | -1.317203 | -1.444304 | 1.616618 | 1.413163 | -0.124628 | 2.059455 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | nn Temporal Discontinuties | 2.086783 | -0.375068 | -1.125189 | -0.108181 | -0.197769 | 0.295903 | 0.645467 | 2.086783 | -0.261586 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 10.709946 | -0.577491 | -1.381134 | -0.549091 | 0.282216 | -0.218540 | -0.521897 | 0.297344 | 10.709946 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 35.845686 | -1.300783 | -1.266579 | -0.010309 | -0.455075 | 6.311743 | 6.222181 | 22.802739 | 35.845686 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 55.601854 | 2.136819 | 1.343575 | -0.160039 | -0.704933 | 16.573601 | 13.550888 | 48.673665 | 55.601854 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | nn Temporal Discontinuties | 1.724959 | -1.085672 | -0.480268 | -0.002702 | 0.022453 | 0.719597 | 0.074985 | -0.200220 | 1.724959 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 13.693569 | -1.436193 | 0.146932 | 0.297627 | -0.895334 | -0.031853 | -0.552044 | 13.693569 | 0.627987 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 31.627271 | -0.514255 | -1.630690 | -0.369303 | 0.378077 | -0.031398 | -0.439570 | 2.340068 | 31.627271 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 14.513027 | -0.229500 | -1.371793 | -0.077978 | -0.181119 | 0.094005 | -0.317467 | 1.803096 | 14.513027 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 9.903250 | -0.767485 | -0.034909 | 0.231554 | -0.549992 | 2.808195 | 0.592458 | 9.903250 | -0.569960 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 7.236491 | -0.103128 | -0.403762 | -0.837233 | -0.459196 | 1.987433 | -0.355210 | 1.100022 | 7.236491 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 7.837576 | 0.077471 | -0.887219 | -0.733705 | -0.616337 | -0.347839 | 0.698155 | 0.137726 | 7.837576 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 11.399778 | -0.124021 | -0.253156 | -0.446498 | -0.721351 | 5.467165 | 3.413469 | 11.399778 | 8.624690 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 13.556504 | -0.357138 | -0.094147 | -0.827760 | 0.173846 | -0.021975 | 0.255894 | 0.381534 | 13.556504 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 4.556629 | -0.879364 | 0.172485 | 0.098233 | -0.442135 | -0.478864 | 0.333374 | 4.556629 | -0.719967 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 3.550737 | 0.355354 | -0.302348 | -0.829650 | -0.139940 | 2.602256 | 3.107132 | 1.841631 | 3.550737 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 10.425166 | -0.536181 | -0.438914 | -0.339955 | -0.479258 | -0.130670 | 2.300674 | 10.425166 | 0.822505 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 3.400272 | -0.394901 | -0.041643 | -0.543360 | -0.671958 | 0.192475 | 0.811400 | 3.400272 | 1.020329 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 13.490380 | 0.188747 | -1.110596 | -0.933839 | 0.616287 | -0.146862 | 0.607607 | 0.708062 | 13.490380 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | ee Temporal Discontinuties | 8.258613 | -0.128359 | -0.472592 | -1.010720 | 0.307634 | 1.454898 | 0.924300 | 1.551020 | 8.258613 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30 | N01 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |